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Interruptive clinical decision support systems, both within and outside of electronic health records, are a resource that should be used sparingly and monitored closely. Excessive use of interruptive alerting can quickly lead to alert fatigue and decreased effectiveness and ignoring of alerts. In this review, we discuss the evidence for effective alert stewardship as well as practices and methods we have found useful to assess interruptive alert burden, reduce excessive firings, optimize alert effectiveness, and establish quality governance at our institutions. We also discuss the importance of a holistic view of the alerting ecosystem beyond the electronic health record.

Background For common infections, previous studies suggest more seasoned prescribers more commonly use inappropriately long antibiotic durations however, there is a paucity of data regarding patient and provider factors associated with antibiotic prescription duration for pediatric skin and soft tissue (SSTI). Methods Retrospective analysis of patients age 0-21 years prescribed enteral antibiotics for cellulitis, abscess, impetigo, or other SSTI in one of 13 Nationwide Children’s Hospital’s primary care clinics in 2020. Encounters for paronychia, facial abscess, and immunocompromised patients were excluded. Based on national and local SSTI guidelines, antibiotic duration was considered inappropriately long if >5 days for cellulitis or drained abscess or >7 days for undrained abscess, impetigo, or other SSTI. Patient and prescriber factors were collected (Table 1) then univariate and multivariable analyses performed to determine which factors were associated with long antibiotic duration. Statistical analyses accounted for within prescriber correlation. Results From 1/1/2020 to 12/31/2020, we identified 1248 encounters for SSTI. After exclusions, 577 encounters with enteral prescriptions written by 89 prescribers were analyzed. Patient age ranged from 11 days to 20 years, 314 (54%) were female, and 497 (86%) had public insurance. The most common diagnosis was impetigo in 165 (29%). Similar rates of long duration were seen across patients of all ages and insurance categories. No difference in prescriber degree type was associated with antibiotic duration. Mean years since completion of medical training for prescribers of long vs guideline concordant prescriptions was 13 vs 10 in univariate analysis (p=.001). In the multivariable analysis, only diagnosis was associated with increased odds of long duration (Table 2). Compared to impetigo, the adjusted odds ratio for inappropriately long duration was 9.36 for cellulitis and 2.03 for abscess. Patient and Prescriber Characteristics for SSTI Antibiotic Prescriptions IQR, interquartile range, MD, Doctor of Medicine, DO, Doctor of Osteopathic Medicine, NP, Nurse Practitioner †Mann Whitney ‡Fisher’s exact *Chi-square ¶N=556 due to missing data for 21 encounters Multivariable Analysis of Patient and Provider Factors and Inappropriately Long Antibiotic Duration for SSTI Multivariable Analysis of Patient and Provider Factors and adjusted odds ratios for inappropriately long antibiotic duration. *Unknown insurance type for 24 encounters †Missing data for 21 encounters Conclusion In this study of antibiotic duration for SSTI, diagnosis of cellulitis was most strongly associated with inappropriately long duration- providing a focus for future stewardship efforts. Contrary to prior studies, no other patient or provider factor was associated with long duration in our pediatric primary care network. Disclosures Jack Stevens, PhD, Colgate Palmolive (although this abstract does not pertain to any products/services of that highly diversified company): Stocks/Bonds|Procter and Gamble (although this abstract does not pertain to any products/services of that highly diversiified company): Stocks/Bonds.

Background Excessive electronic health record (EHR) alerts reduce the salience of actionable alerts. Little is known about the frequency of interruptive alerts across health systems and how the choice of metric affects which users appear to have the highest alert burden. Objective (1) Analyze alert burden by alert type, care setting, provider type, and individual provider across 6 pediatric health systems. (2) Compare alert burden using different metrics. Materials and Methods We analyzed interruptive alert firings logged in EHR databases at 6 pediatric health systems from 2016–2019 using 4 metrics: (1) alerts per patient encounter, (2) alerts per inpatient-day, (3) alerts per 100 orders, and (4) alerts per unique clinician days (calendar days with at least 1 EHR log in the system). We assessed intra- and interinstitutional variation and how alert burden rankings differed based on the chosen metric. Results Alert burden varied widely across institutions, ranging from 0.06 to 0.76 firings per encounter, 0.22 to 1.06 firings per inpatient-day, 0.98 to 17.42 per 100 orders, and 0.08 to 3.34 firings per clinician day logged in the EHR. Custom alerts accounted for the greatest burden at all 6 sites. The rank order of institutions by alert burden was similar regardless of which alert burden metric was chosen. Within institutions, the alert burden metric choice substantially affected which provider types and care settings appeared to experience the highest alert burden. Conclusion Estimates of the clinical areas with highest alert burden varied substantially by institution and based on the metric used.

Background Increased adoption of electronic health records (EHR) with integrated clinical decision support (CDS) systems has reduced some sources of error but has led to unintended consequences including alert fatigue. The “pop-up” or interruptive alert is often employed as it requires providers to acknowledge receipt of an alert by taking an action despite the potential negative effects of workflow interruption. We noted a persistent upward trend of interruptive alerts at our institution and increasing requests for new interruptive alerts. Objectives Using Institute for Healthcare Improvement (IHI) quality improvement (QI) methodology, the primary objective was to reduce the total volume of interruptive alerts received by providers. Methods We created an interactive dashboard for baseline alert data and to monitor frequency and outcomes of alerts as well as to prioritize interventions. A key driver diagram was developed with a specific aim to decrease the number of interruptive alerts from a baseline of 7,250 to 4,700 per week (35%) over 6 months. Interventions focused on the following key drivers: appropriate alert display within workflow, clear alert content, alert governance and standardization, user feedback regarding overrides, and respect for user knowledge. Results A total of 25 unique alerts accounted for 90% of the total interruptive alert volume. By focusing on these 25 alerts, we reduced interruptive alerts from 7,250 to 4,400 per week. Conclusion Systematic and structured improvements to interruptive alerts can lead to overall reduced interruptive alert burden. Using QI methods to prioritize our interventions allowed us to maximize our impact. Further evaluation should be done on the effects of reduced interruptive alerts on patient care outcomes, usability heuristics on cognitive burden, and direct feedback mechanisms on alert utility.

Burnout is a response to sustained job stressors manifesting as a classic triad of emotional exhaustion, depersonalization, and a sense of reduced accomplishment. With 42% of physicians demonstrating some symptoms of burnout, this has already reached epidemic proportions. The COVID-19 pandemic has only worsened this phenomenon.

Objective: To evaluate the safety of computerized physician order entry (CPOE) and associated clinical decision support (CDS) systems in electronic health record (EHR) systems at pediatric inpatient facilities in the US using the Leapfrog Group’s pediatric CPOE evaluation tool.Methods: The Leapfrog pediatric CPOE evaluation tool, a previously validated tool to assess the ability of a CPOE system to identify orders that could potentially lead to patient harm, was used to evaluate 41 pediatric hospitals over a 2-year period. Evaluation of the last available test for each institution was performed, assessing performance overall as well as by decision support category (eg, drug-drug, dosing limits). Longitudinal analysis of test performance was also carried out to assess the impact of testing and the overall trend of CPOE performance in pediatric hospitals.Results: Pediatric CPOE systems were able to identify 62% of potential medication errors in the test scenarios, but ranged widely from 23–91% in the institutions tested. The highest scoring categories included drug-allergy interactions, dosing limits (both daily and cumulative), and inappropriate routes of administration. We found that hospitals with longer periods since their CPOE implementation did not have better scores upon initial testing, but after initial testing there was a consistent improvement in testing scores of 4 percentage points per year.Conclusions: Pediatric computerized physician order entry (CPOE) systems on average are able to intercept a majority of potential medication errors, but vary widely among implementations. Prospective and repeated testing using the Leapfrog Group’s evaluation tool is associated with improved ability to intercept potential medication errors.

O RIGINAL C ONTRIBUTION Building a Natural Language Processing Tool to Identify Patients With High Clinical Suspicion for Kawasaki Disease from Emergency Department Notes Son Doan, PhD, Cleo K. Maehara, MD, MMSc, Juan D. Chaparro, MD, Sisi Lu, MS, Ruiling Liu, MS, Amanda Graham, MPH, Erika Berry, Chun-Nan Hsu, PhD, John T. Kanegaye, MD, David D. Lloyd, MD, Lucila Ohno-Machado, MD, Jane C. Burns, MD, Adriana H. Tremoulet, MD, MAS, and the Pediatric Emergency Medicine Kawasaki Disease Research Group Abstract Objective: Delayed diagnosis of Kawasaki disease (KD) may lead to serious cardiac complications. We sought to create and test the performance of a natural language processing (NLP) tool, the KD-NLP, in the identification of emergency department (ED) patients for whom the diagnosis of KD should be considered. Methods: We developed an NLP tool that recognizes the KD diagnostic criteria based on standard clinical terms and medical word usage using 22 pediatric ED notes augmented by Unified Medical Language System vocabulary. With high suspicion for KD defined as fever and three or more KD clinical signs, KD-NLP was applied to 253 ED notes from children ultimately diagnosed with either KD or another febrile illness. We evaluated KD-NLP performance against ED notes manually reviewed by clinicians and compared the results to a simple keyword search. Results: KD-NLP identified high-suspicion patients with a sensitivity of 93.6% and specificity of 77.5% compared to notes manually reviewed by clinicians. The tool outperformed a simple keyword search (sensitivity = 41.0%; specificity = 76.3%). Conclusions: KD-NLP showed comparable performance to clinician manual chart review for identification of pediatric ED patients with a high suspicion for KD. This tool could be incorporated into the ED electronic health record system to alert providers to consider the diagnosis of KD. KD-NLP could serve as a model for decision support for other conditions in the ED. ACADEMIC EMERGENCY MEDICINE 2016;23:628–636 © 2016 by the Society for Academic Emergency Medicine From the Department of Biomedical Informatics, University of California (SD, CKM, JDC, CNH, LOM), San Diego, CA; the Depart- ment of Computer Science, University of Pittsburgh (SL), Pittsburgh, PA; The University of Texas Health Science Center at Hous- ton (RL), Houston, TX; Children’s Healthcare of Atlanta (AG, DDL), Atlanta, GA; the Department of Pediatrics, University of California at San Diego (EB, JTK, JCB, AHT, PEMKDRG), La Jolla, CA; Rady Children’s Hospital San Diego (JTK, JCB, AHT, PEMKDRG), San Diego, CA; and the Emory University School of Medicine (DDL), Atlanta, GA. Members of the Pediatric Emergency Medicine Kawasaki Disease Research Group included Lindsay T. Grubensky, RN, MSN, CPNP-PC, Jim R. Harley, MD, MPH, Paul Ishimine, MD, Jamie Lien, MD, Simon J. Lucio, MD, Seema Shah, MD, and Stacey Ulrich, MD. Received August 4, 2015; revision received November 29, 2015; accepted December 30, 2015. Part of this work was presented in poster format at the Pediatric Academic Societies Annual Meeting in San Diego, CA, on April This work was supported in part by the Patient-Centered Outcomes Research Institute (PCORI), contract CDRN-1306-04819 and NIH grant U54HL108460. The authors have no potential conflicts to disclose. Supervising Editor: Damon Kuehl, MD. Address for correspondence and reprints: Adriana H. Tremoulet; e-mail: atremoulet@ucsd.edu. ISSN 1069-6563 PII ISSN 1069-6563583 © 2016 by the Society for Academic Emergency Medicine doi: 10.1111/acem.12925

Introduction: Delays in hospital discharge can negatively impact patient care, bed availability, and patient satisfaction. There are limited studies examining how the electronic health record (EHR) can be used to improve discharge timeliness. This study aimed to implement an EHR discharge optimization tool (DOT) successfully and achieve a discharge before noon (DBN) percentage of 25%. Methods: We conducted a single-center quality improvement study of patients discharged from 3 pediatric hospital medicine teaching service teams at a quaternary care academic children’s hospital. The multidisciplinary team created a DOT centrally embedded within the care team standard workflow to communicate anticipated time until discharge. The primary outcome was the monthly percentage of patients discharged before noon. Secondary outcomes included provider utilization of the DOT, tool accuracy, and patient length of stay. Balancing measures were 7- and 30-day readmission rates. Results: The DBN percentage increased from 16.4% to an average of 19.3% over the 13-month intervention period (P = 0.0005). DOT utilization was measured at 87.2%, and the overall accuracy of predicting time until discharge was 75.6% (P < 0.0001). Median length of stay declined from 1.75 to 1.68 days (P = 0.0033), and there was no negative impact on 7- or 30-day readmission rates. Conclusion: This initiative demonstrated that a highly utilized and accurate discharge tool could be created in the EHR to assist medical care teams with improving DBN percentage on busy, academic teaching services.

Background: Childhood obesity is a significant problem, with prevalence rates as high as 17%. In addition to long-term health effects such as metabolic syndrome and coronary artery disease, pediatric obesity also presents immediate health and safety risks such as operative complications, difficult airways and medication dosing errors. Large-scale pediatric databases such as the Pediatric Health Information System, drawn primarily from ICD-9/10 codes, may significantly underestimate the prevalence of obesity in the pediatric inpatient and outpatient setting. One recent study in hospitalized children found that discharge ICD-9 codes underestimated the …

Background: Stress is a contributing factor to many major health problems in the United States, such as heart disease, depression, and autoimmune diseases. Relaxation is often recommended in mental health treatment as a frontline strategy to reduce stress, thereby improving health conditions. Objective: The objective of our study was to understand how people express their feelings of stress and relaxation through Twitter messages. Methods: We first performed a qualitative content analysis of 1326 and 781 tweets containing the keywords "stress" and "relax", respectively. We then investigated the use of machine learning algorithms to automatically classify tweets as stress versus non stress and relaxation versus non relaxation. Finally, we applied these classifiers to sample datasets drawn from 4 cities with the goal of evaluating the extent of any correlation between our automatic classification of tweets and results from public stress surveys. Results: Content analysis showed that the most frequent topic of stress tweets was education, followed by work and social relationships. The most frequent topic of relaxation tweets was rest and vacation, followed by nature and water. When we applied the classifiers to the cities dataset, the proportion of stress tweets in New York and San Diego was substantially higher than that in Los Angeles and San Francisco. Conclusions: This content analysis and infodemiology study revealed that Twitter, when used in conjunction with natural language processing techniques, is a useful data source for understanding stress and stress management strategies, and can potentially supplement infrequently collected survey-based stress data., 38 pages,12 figures, 6 tables, 5 Appendix (full version) -- shorter version published in JMIR Public Health Surveill 2017;3(2):e35

Parasitic diseases, previously thought to be the domain of developing nations only, are being increasingly recognized as a significant source of morbidity/mortality in developed and developing nations alike. While many parasites cause long-term low-level disease, some parasitic diseases can have severe manifestations necessitating intensive care unit admission. In this review, we focus on severe malaria (including cerebral malaria), neurocysticercosis, Strongyloides hyperinfection syndrome, American trypanosomiasis (Chagas disease), baylisascariasis and amoebic meningoencephalitis.

Background The mainstay of toxoplasmosis treatment targets the folate biosynthetic pathways and has not changed for the last 50 years. The activity of these chemotherapeutic agents is restricted to one lifecycle stage of Toxoplasma gondii, they have significant toxicity, and the impending threat of emerging resistance to these agents makes the discovery of new therapies a priority. We now demonstrate that auranofin, an orally administered gold containing compound that was FDA approved for treatment of rheumatoid arthritis, has activity against Toxoplasma gondii in vitro (IC50 = 0.28 µM) and in vivo (1 mg/kg). Methods/Principal Findings Replication within human foreskin fibroblasts of RH tachyzoites was inhibited by auranofin. At 0.4 µM, auranofin inhibited replication, as measured by percent infected fibroblasts at 24 hrs, (10.94% vs. 24.66% of controls; p = 0.0003) with no effect on parasite invasion (16.95% vs. 12.91% p = 0.4331). After 18 hrs, 62% of extracellular parasites treated with auranofin were non-viable compared to control using an ATP viability assay (p = 0.0003). In vivo, a previously standardized chicken embryo model of acute toxoplasmosis was used. Fourteen day old chicken embryos were injected through the chorioallantoic vein with 1×104 tachyzoites of the virulent RH strain. The treatment group received one dose of auranofin at the time of inoculation (1 mg/kg estimated body weight). On day 5, auranofin-treated chicken embryos were 100% protected against death (p = 0.0002) and had a significantly reduced parasite load as determined by histopathology, immunohistochemistry and by the number of parasites quantified by real-time PCR. Conclusions These results reveal in vitro and in vivo activity of auranofin against T. gondii, suggesting that it may be an effective alternative treatment for toxoplasmosis., Author Summary Toxoplasma gondii is a protozoan parasite that infects at least two thirds of the world human population. Once it infects the human host, it has great predilection for the brain and the retina of the eye. It remains latent until the host's immune system weakens, and then causes organ tissue damage. There are very few treatments available that are active against this parasite, and they all fail to eradicate it from the human body. Hence, there is always a risk for recurrence and/or disabling long-term complications such as blindness or neurological abnormalities. Despite this fact, it has been over fifty years since most anti-Toxoplasma agents were initially described. Most recently, in an attempt to expedite the process of drug discovery, older drugs are making a comeback by being re-purposed for new diseases. Auranofin, which was originally designed to treat rheumatoid arthritis, has consistently shown antiparasitic activity against multiple organisms, including parasites of great public health importance such as Plasmodium, Schistosoma and Leishmania, although most of these reports are based on in vitro assays. Herein, we present our studies that demonstrate that auranofin is active against Toxoplasma gondii in vitro and in an animal model of acute Toxoplasma infection, suggesting that auranofin has great potential to become a new anti-Toxoplasma agent.